Predicting Public Opinion Reversal Based on Evolution Analysis of Events and Improved KE-SMOTE Algorithm
Wang Nan1,2,Li Hairong1(),Tan Shuru3
1School of Management Science and Information Engineering, Jilin University of Finance and Economics, Changchun 130117, China 2Institute of Economic Information Management, Jilin University of Finance and Economics, Changchun 130117, China3College of Information Science and Engineering, Guilin University of Technology, Guilin 541006, China
[Objective] This paper tries to accurately predict online public opinion reversal. [Methods] First, we retrieved the features of public opinion events based on their evolution characteristics and development process before the reversal points. Then, we used the improved KE-SMOTE algorithm to create an automatic optimization process, which balanced the event set with very skewed positive and negative samples. We also constructed a neural network ensemble learning model using the balanced event set. Finally, we examined our model with 30 trending public opinion events from 2021, and discussed the causes of errors for the inconsistent prediction results. We also provided corresponding countermeasures and suggestions on avoiding the reversal of public opinion. [Results] We found that the prediction accuracy of the proposed model on the test sets reached 99.7%, and all reversal events were predicted. [Limitations] While the time interval becoming much shorter between the occurrence and reversal of public opinion events, more research is needed to examine the proposed model with smaller data sets. [Conclusions] Our new model can accurately identify the public opinion reversal events in advance.
王楠, 李海荣, 谭舒孺. 基于舆情事件演化分析及改进KE-SMOTE算法的舆情反转预测研究*[J]. 数据分析与知识发现, 2022, 6(2/3): 396-408.
Wang Nan, Li Hairong, Tan Shuru. Predicting Public Opinion Reversal Based on Evolution Analysis of Events and Improved KE-SMOTE Algorithm. Data Analysis and Knowledge Discovery, 2022, 6(2/3): 396-408.
( Xiao Jinke, Li Guosong. Analysis of the Evolution of Public Opinion on the Network of University Emergency — Taking the “Wuhan Software Engineering Vocational School’s Dormitory was Requisitioned” as an Example[J]. Journal of News Research, 2020, 11(11):52-53.)
( Liu Yuxiao, Yang Liping. Research on the Relationship Mechanism Between News Reversal and Public Opinion Reversal in the New Media Era — Based on Three Cases of Reversal News[J]. North Media Research, 2021(2):61-67.)
( Hu Wenzhao. Perspective on the Causes of Public Opinion Reversal in the Online Donation Event from the“Luo Yixiao Event”[J]. Journal of News Research, 2017, 8(3):271-272.)
( Han Yunrong. Causes and Treatment of Public Opinion Reversal — Through a Comparative Analysis of News Reversal[J]. People’s Tribune, 2019(30):116-118.)
( Wang Nan, Li Hairong, Tan Shuru. Predicting of Public Opinion Reversal with Improved SMOTE Algorithm and Ensemble Learning[J]. Data Analysis and Knowledge Discovery, 2021, 5(4):37-48.)
[7]
郑玮. 舆情反转现象的推动机制研究[D]. 哈尔滨: 黑龙江大学, 2020.
[7]
( Zheng Wei. Research on the Reversal Mechanism of Public Opinion[D]. Harbin: Heilongjiang University, 2020.)
[8]
孙翠平. 网络舆情反转的传播及演化研究[D]. 广州: 华南理工大学, 2018.
[8]
( Sun Cuiping. A Study on the Spread and Evolution of Internet Public Opinion Reversal[D]. Guangzhou: South China University of Technology, 2018.)
( Tian Junjing, Lan Yuexin, Xia Yixue, et al. Recognition and Empirical Study of Network Public Opinion Reversal Based on Decision Tree Method[J]. Journal of Intelligence, 2019, 38(8):121-125,171.)
( Tian Shihai, Sun Meiqi, Zhang Jiayu. Prediction of We-Media Public Opinion Reversion Based on Bayesian Network[J]. Information Studies: Theory & Application, 2019, 42(2):127-133.)
( Jiang Yesha. How the Truth Approaches the Truth in the Post-Truth Era--An Analysis of Public Opinion Based on the Food Safety Incident in Chengdu No.7 Experimental School[J]. Southeast Communication, 2019(10):91-93.)
( Luo Zhenglin, Wen Xin. Communication Mechanism of “Reversal News” in the Post-Truth Era and Its Social Regulation[J]. Media Observer, 2019(12):5-13.)
( Zhang Li, Zhu Hou, Wan Fangbin, et al. Simulation of Public Opinion Reversal Phenomenon Considering the Effects of Information and Organization Atmosphere[J]. Information Science, 2018, 36(5):57-63.)
[15]
Zhu H, Hu B. Impact of Information on Public Opinion Reversal—An Agent Based Model[J]. Physica A: Statistical Mechanics and Its Applications, 2018, 512:578-587.
doi: 10.1016/j.physa.2018.08.085
( Yuan Ye, Lan Yuexin, Zhang Peng, et al. Research on the Classification and Forecast of Reversal Network Public Opinion Based on Cluster Analysis[J]. Information Science, 2017, 35(9):54-60.)
( Xia Yixue, Lan Yuexin, Liu Mo, et al. Inversion Mechanism and Prediction of Network Public Opinion in Big Data Environment[J]. Journal of Intelligence, 2018, 37(8):92-96,207.)
( Jiang Changbin, Zou Yueqi, Wang Hu, et al. Research on Prediction for Reversal of We-Media Public Opinion Based on SVM[J]. Information Science, 2021, 39(4):47-53.)
[20]
阮紫玥. 新媒体网络舆情反转预测研究[D]. 武汉: 华中师范大学, 2019.
[20]
( Ruan Ziyue. Research on Public Opinion Reversal Prediction Model in New Media Environment[D]. Wuhan: Central China Normal University, 2019.)
[21]
Judd C M, Park B. Definition and Assessment of Accuracy in Social Stereotypes[J]. Psychological Review, 1993, 100(1):109-128.
pmid: 8426877
( Tang Shengzhuo. Analysis on the Process of Intensification of Social Contradictions from the Perspective of Schramm’s Mass Communication[J]. News Research, 2021(3):79-86.)
